An intelligent matching method for the equivalent circuit of electrochemical impedance spectroscopy based on Random Forest

doi:10.1016/j.jmst.2024.05.024

IMR OpenIR

	An intelligent matching method for the equivalent circuit of electrochemical impedance spectroscopy based on Random Forest
	Chen, Wenbo 1,2,3,4; Yan, Bingjun 1,2,3; Xu, Aidong 1,2,3; Mu, Xin 5; Zhou, Xiufang 1,2,3,4; Jiang, Maowei 1,2,3,4; Wang, Changgang 5; Li, Rui 6; Huang, Jie 6; Dong, Junhua 5
通讯作者	Xu, Aidong(xad@sia.cn) ; Dong, Junhua(jhdong@imr.ac.cn)
	2025-02-20
发表期刊	JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
ISSN	1005-0302
卷号	209 页码:300-310
摘要	One of the core works of analyzing Electrochemical Impedance Spectroscopy (EIS) data is to select an appropriate equivalent circuit model to quantify the parameters of the electrochemical reaction process. However, this process often relies on human experience and judgment, which will introduce subjectivity and error. In this paper, an intelligent approach is proposed for matching EIS data to their equivalent circuits based on the Random Forest algorithm. It can automatically select the most suitable equivalent circuit model based on the characteristics and patterns of EIS data. Addressing the typical scenario of metal corrosion, an atmospheric corrosion EIS dataset of low -carbon steel is constructed in this paper, which includes five different corrosion scenarios. This dataset was used to validate and evaluate the proposed method in this paper. The contributions of this paper can be summarized in three aspects: (1) This paper proposes a method for selecting equivalent circuit models for EIS data based on the Random Forest algorithm. (2) Using authentic EIS data collected from metal atmospheric corrosion, the paper establishes a dataset encompassing five categories of metal corrosion scenarios. (3) The superiority of the proposed method is validated through the utilization of the established authentic EIS dataset. The experiment results demonstrate that, in terms of equivalent circuit matching, this method surpasses other machine learning algorithms in both precision and robustness. Furthermore, it shows strong applicability in the analysis of EIS data. (c) 2024 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.
关键词	Electrochemical impedance spectroscopy Random forest Corrosion Equivalent circuit model
资助者	National Key R&D Program of China
DOI	10.1016/j.jmst.2024.05.024
收录类别	SCI
语种	英语
资助项目	National Key R&D Program of China[2022YFB3207603]
WOS研究方向	Materials Science ; Metallurgy & Metallurgical Engineering
WOS类目	Materials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering
WOS记录号	WOS:001259192200001
出版者	JOURNAL MATER SCI TECHNOL
引用统计
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/187745
专题	中国科学院金属研究所
通讯作者	Xu, Aidong; Dong, Junhua
作者单位	1.Chinese Acad Sci, Key Lab Networked Control Syst, Shenyang 110169, Peoples R China 2.Chinese Acad Sci, Shenyang Inst Automat, Shenyang 110169, Peoples R China 3.Chinese Acad Sci, Inst Robot & Intelligent Mfg, Shenyang 110169, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Chinese Acad Sci, Inst Met Res, Shenyang Natl Lab Mat Sci, Shenyang 110016, Peoples R China 6.China Oil & Gas Pipeline Network Corp, Gen Res Inst, Langfang 065000, Peoples R China
推荐引用方式 GB/T 7714	Chen, Wenbo,Yan, Bingjun,Xu, Aidong,et al. An intelligent matching method for the equivalent circuit of electrochemical impedance spectroscopy based on Random Forest[J]. JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY,2025,209:300-310.
APA	Chen, Wenbo.,Yan, Bingjun.,Xu, Aidong.,Mu, Xin.,Zhou, Xiufang.,...&Dong, Junhua.(2025).An intelligent matching method for the equivalent circuit of electrochemical impedance spectroscopy based on Random Forest.JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY,209,300-310.
MLA	Chen, Wenbo,et al."An intelligent matching method for the equivalent circuit of electrochemical impedance spectroscopy based on Random Forest".JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY 209(2025):300-310.